chore: clean up content phase organization

apps/docs/content/(04-relational)/graph-dfs/133-clone-graph.mdx

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+---
+title: '133. Clone Graph'
+description: Given a reference of a node in a connected undirected graph
+sidebar:
+  label: 'Clone Graph'
+  badge: 'Medium'
+---
+
+<Badge variant="accent">Hash Table</Badge>
+
+### Example 1:
+- Input: `adjList = [[2,4],[1,3],[2,4],[1,3]]`
+- Output: `[[2,4],[1,3],[2,4],[1,3]]`
+- Explanation: There are `4` nodes in the graph. 1st `node` (val = 1)'s neighbors are 2nd `node` (val = `2`) and 4th `node` (val = `4`). 2nd `node` (val = 2)'s neighbors are 1st `node` (val = `1`) and 3rd `node` (val = `3`). 3rd `node` (val = 3)'s neighbors are 2nd `node` (val = `2`) and 4th `node` (val = `4`). 4th `node` (val = 4)'s neighbors are 1st `node` (val = `1`) and 3rd `node` (val = `3`).
+
+### Example 2:
+- Input: `adjList = [[]]`
+- Output: `[[]]`
+- Explanation: Note that the input contains one empty list. The graph consists of only one `node` with val = `1` and it does not have any neighbors.
+
+### Example 3:
+- Input: `adjList = []`
+- Output: `[]`
+- Explanation: This an empty graph, it does not have any nodes.
+
+### Constraints:
+
+- The number of nodes in the graph is in the range [0, 100].
+- `1 <= Node.val <= 100`
+- Node.val is unique for each node.
+- There are no repeated edges and no self-loops in the graph.
+- The Graph is connected and all nodes can be visited starting from the given node.
+
+## Solution
+
+```py
+"""
+# Definition for a Node.
+class Node:
+    def __init__(self, val = 0, neighbors = None):
+        self.val = val
+        self.neighbors = neighbors if neighbors is not None else []
+"""
+
+from typing import Optional
+
+
+class Solution:
+    def cloneGraph(self, node: Optional["Node"]) -> Optional["Node"]:
+        oldToNew = {}
+
+        def dfs(node):
+            if node in oldToNew:
+                return oldToNew[node]
+
+            copy = Node(node.val)
+            oldToNew[node] = copy
+
+            for n in node.neighbors:
+                copy.neighbors.append(dfs(n))
+            return copy
+
+        return dfs(node) if node else None
+```